Triple

T14713484
Position Surface form Disambiguated ID Type / Status
Subject Asa Butterfield E345615 entity
Predicate notableWork P4 FINISHED
Object Hugo E138723 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Hugo | Statement: [Asa Butterfield, notableWork, Hugo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hugo
Context triple: [Asa Butterfield, notableWork, Hugo]
  • A. Hugo
    Hugo is a masculine given name of Germanic origin, commonly used in various European and Spanish-speaking countries.
  • B. Hugo chosen
    Hugo is a 2011 fantasy adventure film directed by Martin Scorsese, acclaimed for its innovative use of 3D and its homage to early cinema and filmmaker Georges Méliès.
  • C. Hugo
    Hugo is a tragic young character from the manga series "Gunnm" (also known as "Battle Angel Alita"), whose dreams of reaching the floating city Zalem drive much of the early emotional narrative.
  • D. HUGO
    HUGO is a contemporary fashion line by Hugo Boss known for its modern, trend-driven clothing and accessories aimed at a younger, style-conscious audience.
  • E. Hugo and the Impossible Thing
    "Hugo and the Impossible Thing" is a children's picture book that follows a determined little dog who inspires his forest friends to tackle a seemingly impossible challenge through courage and teamwork.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d822e4a8c08190a155df736bb7bc13 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb982bf248190881e21a8a0861a3f completed April 14, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf08f2aa08190a5ac3240d1de90fb completed May 8, 2026, 2:17 p.m.
Created at: April 10, 2026, 1:29 a.m.